The Law of Large Numbers

The Law of Large Numbers states that as you repeat an experiment or trial many times, the average result will tend to get closer to the expected or true value. For example, flipping a fair coin many times will result in the proportion of heads approaching 50%. This principle helps us trust statistical averages because, with enough repetitions, the outcomes become more predictable and representative of the overall likelihood, reducing the effect of randomness in small samples. It underscores the idea that larger data sets lead to more reliable estimates of probabilities.